cd ../dev/ecoop/trunk/python/
/home/epy/dev/ecoop/trunk/python
from esrutil import svnup
svnup()
Code updated to version number 7790
from esrutil import getID, getResults, makeQrCode, GUI
from driver import Driver as d
from driver import Driver as d
d = d()
ID = getID('epitest')
your session ID is : epitest_Wednesday_07_November_2012_09_10_00_PM
%pylab inline
Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline]. For more information, type 'help(pylab)'.
nao = d.getnao(output=ID, web=True)
d.plotDriver(nao, ptype='bar', name='nao', nb='y', xticks=20, xticks_fontsize=20, dateformat=True,
figsize=(5,3), xmargin=True, ymargin=True, legend=True, output=ID, dpi=600,
grid=True, ylabel='Mean anomaly', title='North Atlantic Oscillation', web=True)
NAO data saved in : epitest_Wednesday_07_November_2012_09_10_00_PM graph saved in: epitest_Wednesday_07_November_2012_09_10_00_PM/nao_bar.png web is true nao_bar.png epitest_Wednesday_07_November_2012_09_10_00_PM
amo = d.getamo(output=ID, web=True)
d.plotDriver(amo, ptype='bar', name='amo', nb='y', xticks=20, xticks_fontsize=20, dateformat=True,
figsize=(5,3), xmargin=True, ymargin=True, legend=True, output=ID, dpi=600,
grid=True, ylabel='Mean anomaly', title='Atlantic Multidecadal Oscillation', web=True)
AMO data saved in : epitest_Wednesday_07_November_2012_09_10_00_PM graph saved in: epitest_Wednesday_07_November_2012_09_10_00_PM/amo_bar.png web is true amo_bar.png epitest_Wednesday_07_November_2012_09_10_00_PM
phytoplancton = d.getPhitoplancton()
diatom = phytoplancton['diatom']
dino = phytoplancton['dino']
d.plotDriver(dino, ptype='point', nb='y', datarange=(1960,2008), xticks=5, xticks_fontsize=20, dateformat=True,
figsize=(5,3), xmargin=True, ymargin=True, legend=True, smooth=(0.2,3), output=ID, dpi=600,
grid=True, xlabel='Year', ylabel='Abundance anomaly', title='Dinoflagellates (1960 - 2008)', web=True)
graph saved in: epitest_Wednesday_07_November_2012_09_10_00_PM/driver_point.png web is true driver_point.png epitest_Wednesday_07_November_2012_09_10_00_PM driver smothed data saved in : epitest_Wednesday_07_November_2012_09_10_00_PM/driver_smooth.csv
d.plotOverlay(data1=nao, data3=dino, data2=diatom,
label2='Diatom', label3='Dinoflagellates', label1='North Atlantic Oscillation',
datarange=(1960,2008), smooth=(0.25,3), aligny=True, grid=True)
-1.5 2.0
import os
os.system('gdal_translate -a_srs "+proj=lcc +lat_1=36.1667 +lat_2=43.8333 +lat_0=40 +lon_0=-70 +x_0=0 +y_0=0 +mo_defs +a=6378206.4 +rf=294.9786982 +to_meter=1" -a_ullr -640000 -640000 640000 640000 -of GTiff -ot Float64 /home/epy/notebook/clh-a.hdf clh-a.tif')
0
os.system('gdalwarp clh-a.tif clh-a-nup.tif')
0
import sys
import grass.script as grass
import grass.script.setup as gsetup
gisbase = os.environ['GISBASE'] = "/usr/local/grass-7.0.svn/"
gisdbase = os.path.join(os.environ['HOME'], "grass7data")
location = "modis"
mapset = "PERMANENT"
sys.path.append(os.path.join(os.environ['GISBASE'], "etc", "python"))
gsetup.init(gisbase, gisdbase, location, mapset)
print grass.gisenv()
{'MAPSET': 'PERMANENT', 'GISDBASE': '/home/epy/grass7data', 'LOCATION_NAME': 'modis'}
grass.run_command('r.in.gdal', input='clh-a-nup.tif', output='clha', flags='oe', overwrite=True)
0
grass.run_command('r.null', map='clha', setnull='inf')
0
color_rules = '''0.03 128:0:133
0.1 19:0:243
0.3 16:175:255
1 34:255:0
3 255:244:0
10 253:71:0
30 253:0:252'''
color = open("color.txt", "wb")
color.write( color_rules);
color.close()
grass.run_command('r.colors', map='clha', rules='color.txt')
0
grass.run_command('r.out.png', input='clha', output='clha-nup.png', flags='w', compression = 9, overwrite=True)
0
from IPython.core.display import Image
Image(filename='clha-nup.png')
info = grass.read_command('r.info', map='clha').split('\n')
info
[' +----------------------------------------------------------------------------+', ' | Layer: clha Date: Wed Nov 7 16:10:07 2012 |', ' | Mapset: PERMANENT Login of Creator: epy |', ' | Location: modis |', ' | DataBase: /home/epy/grass7data |', ' | Title: ( clha ) |', ' | Timestamp: none |', ' |----------------------------------------------------------------------------|', ' | |', ' | Type of Map: raster Number of Categories: 136 |', ' | Data Type: FCELL |', ' | Rows: 1024 |', ' | Columns: 1024 |', ' | Total Cells: 1048576 |', ' | Projection: Lambert Conformal Conic |', ' | N: 640000 S: -640000 Res: 1250 |', ' | E: 640000 W: -640000 Res: 1250 |', ' | Range of data: min = 0.01381789 max = 135.7432 |', ' | |', ' | Data Description: |', ' | generated by r.in.gdal |', ' | |', ' | Comments: |', ' | r.in.gdal -o -e input="clh-a-nup.tif" output="clha" offset=0 |', ' | |', ' +----------------------------------------------------------------------------+', '', '']
from IPython.core.display import Image
Image(filename='../../../../notebook/ices_map.png')
amo = d.getamo(output=ID)
nin = d.getnin(output=ID)
nao = d.getnao(output=ID)
climate = d.Df(output=ID, frmt='csv')
d.mplotIndex(climate, output=ID)
climate.describe()
AMO data saved in : epitest_Wednesday_07_November_2012_09_10_00_PM NIN data saved in : epitest_Wednesday_07_November_2012_09_10_00_PM NAO data saved in : epitest_Wednesday_07_November_2012_09_10_00_PM graph saved in: epitest_Wednesday_07_November_2012_09_10_00_PM/climate.png
AMO | NAO | NIN | |
---|---|---|---|
count | 156.000000 | 148.000000 | 30.000000 |
mean | -0.001097 | 0.148581 | -0.000000 |
std | 0.179609 | 1.940747 | 1.000000 |
min | -0.418333 | -4.890000 | -1.689705 |
25% | -0.131979 | -1.047500 | -0.900031 |
50% | 0.014542 | 0.235000 | 0.191878 |
75% | 0.122188 | 1.540000 | 0.599686 |
max | 0.450500 | 5.080000 | 1.945570 |
#GUI(ID)
from esrutil import saveNotebook
nb_name = 'ICES_Poster.ipynb'
saveNotebook(ID, nb_name, web=True)
saveNotebook(ID, nb_name, web=True)
d.makepdf(ID=ID, nbname='ICES_Poster.ipynb')
getResults(ID)
results are now available for download at : http://tw.rpi.edu/media/2013/09/25/10ff/epitest_Wednesday_07_November_2012_09_10_00_PM.zip
qrimage = makeQrCode(ID)
Image(filename=qrimage)